Regional Capability–Resource Alignment for Sustainable Bioenergy Transitions: Structural Sorting and Place-Based Pathways in China

Biomass-based energy transitions depend not only on resource availability but also on whether regional capabilities match the material and organisational requirements of different feedstocks. Using a balanced panel of 30 Chinese provinces during 2012–2022, this study treats New Quality Productive Forces (NQPF) as a proxy for regional productive and innovative capabilities and examines their association with five theoretical biomass resource potentials. Two-way fixed effects, a stacked province–resource–year model, a Mundlak Within–Between decomposition, province-specific trend checks, small-cluster inference, multiplicity adjustment, and a provincial diagnostic typology are combined to distinguish aggregate relationships, resource-specific heterogeneity, and persistent cross-provincial structure. Under the baseline entropy-weighted specification, aggregate NQPF is positively associated with theoretical carbon-mitigation potential, but the association is attenuated by province-specific trends and is not reproduced by equal-weight or PCA re-aggregations. At the resource level, New Modes–agricultural residues and New Industries–livestock manure retain nominal support under wild-cluster inference but not family-level multiplicity adjustment. The strongest multiplicity-adjusted evidence concerns overall cross-resource differentiation for New Drivers and is persistent between structural sorting for New Industries, whose long-term provincial mean is negatively associated with agricultural residues, forestry and orchard residues, livestock manure, and wastewater biomass and positively associated with municipal solid waste. Component-level patterns are therefore treated as exploratory. A 2022 four-quadrant typology further shows that capability–resource configurations are resource-specific, with livestock manure displaying the most gap-type configurations and municipal solid waste showing the strongest tendency toward same-direction capability–resource configurations. Capability–resource alignment is thus best treated as an ex ante screening condition rather than a causal or project-readiness measure; ecological retention, competing uses, lifecycle performance, circularity, logistics, finance, and governance remain necessary sustainability filters.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-10-28
DOI
https://doi.org/10.3390/su182110975
Primary Topic
Bioeconomy and Sustainability Development
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Regional Capability–Resource Alignment for Sustainable Bioenergy Transitions: Structural Sorting and Place-Based Pathways in China

Ying Han, Yuehong Zhu, Dongjun Wang
2 links
Sustainability
Bioeconomy and Sustainability Development
article

Regional Capability–Resource Alignment for Sustainable Bioenergy Transitions: Structural Sorting and Place-Based Pathways in China

Ying Han, Yuehong Zhu, Dongjun Wang
article en

Abstract

Biomass-based energy transitions depend not only on resource availability but also on whether regional capabilities match the material and organisational requirements of different feedstocks. Using a balanced panel of 30 Chinese provinces during 2012–2022, this study treats New Quality Productive Forces (NQPF) as a proxy for regional productive and innovative capabilities and examines their association with five theoretical biomass resource potentials. Two-way fixed effects, a stacked province–resource–year model, a Mundlak Within–Between decomposition, province-specific trend checks, small-cluster inference, multiplicity adjustment, and a provincial diagnostic typology are combined to distinguish aggregate relationships, resource-specific heterogeneity, and persistent cross-provincial structure. Under the baseline entropy-weighted specification, aggregate NQPF is positively associated with theoretical carbon-mitigation potential, but the association is attenuated by province-specific trends and is not reproduced by equal-weight or PCA re-aggregations. At the resource level, New Modes–agricultural residues and New Industries–livestock manure retain nominal support under wild-cluster inference but not family-level multiplicity adjustment. The strongest multiplicity-adjusted evidence concerns overall cross-resource differentiation for New Drivers and is persistent between structural sorting for New Industries, whose long-term provincial mean is negatively associated with agricultural residues, forestry and orchard residues, livestock manure, and wastewater biomass and positively associated with municipal solid waste. Component-level patterns are therefore treated as exploratory. A 2022 four-quadrant typology further shows that capability–resource configurations are resource-specific, with livestock manure displaying the most gap-type configurations and municipal solid waste showing the strongest tendency toward same-direction capability–resource configurations. Capability–resource alignment is thus best treated as an ex ante screening condition rather than a causal or project-readiness measure; ecological retention, competing uses, lifecycle performance, circularity, logistics, finance, and governance remain necessary sustainability filters.

SustainabilityVol. 18(21)
Nanjing University (CN), Northeastern University (CN)
Fundamental Research Funds for the Central Universities
Affordable and clean energy, Climate action, Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Bioeconomy and Sustainability Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon